Early detection of Parkinson's disease in the NAKO Health Study (NAKO-PPD)

• Applicant: Privatdozent Dr. Sebastian Heinzel
• Subject Area: Epidemiology and Medical Biometry/Statistics ; Clinical Neurology; Neurosurgery and Neuroradiology ; Public Health, Healthcare Research, Social and Occupational Medicine
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 530948794

Parkinson's disease (PD) is characterized by a prodromal phase in which neurodegenerative processes occur years before clinical PD diagnosis. As evidenced by numerous prospective studies, risk and prodromal markers can be predictive of PD and used for early detection. The International Parkinson and Movement Disorder Society (MDS) has reviewed and compiled evidence of the predictive values of markers and proposed a Bayesian classifier as a research tool that can calculate the probability of prodromal PD (PPD) in an individual using age, individual marker profiles, and the evidence-based predictive values of the markers. Thus, the MDS criteria can identify individuals as at-risk (50-79% probability) or high-risk (>80%) PPD. This approach has been validated in several clinical cohorts, but it is still unclear how valid the early detection of PD using the MDS criteria is in population-based prospective studies. The NAKO Health Study (NAKO) is the largest population-based cohort study in Germany and has already collected data on most MDS criteria markers for PD, including 7 risk and 8 prodromal markers, in 110,256 individuals aged 50 years or older during the baseline examination. The second examination of NAKO, 5 years after the baseline examination, can reveal which individuals were actually diagnosed with incident PD during the follow-up period. The NAKO-PPD project will (1) calculate the PPD probability of older NAKO participants during the baseline examination and (2) investigate the validity of the early detection approach using accuracy measures such as the positive predictive value. (3) At-risk/high-risk individuals, incident PD cases, and control subjects will be compared exploratively regarding clinical variables/diseases, lifestyle, blood-based biomarkers, wearable movement sensor measures, and other factors. This will help identify new predictive markers as well as modifiable and protective factors for PD. (4) Statistical marker interactions and age- and sex-dependent predictive values of the markers will be explored to improve PD prediction models in the future. (5) The characteristics of established and new markers in incident PD cases that were not identified as high-risk individuals will be investigated to define possible subtypes of PPD and identify approaches to improve the sensitivity of the early detection of PD. The NAKO-PPD project aims to demonstrate the validity and potential for improvement of an established approach for the early detection of PD using a large, German, population-based, prospective dataset. Additionally, completely new predictive and protective aspects of the prodrome of PD could be identified. As a large number of the collected markers are (theoretically) accessible to general practitioners, the project represents an important step toward a widespread and actionable early detection of PD in the general population.

• DFG Programme: Research Grants
• Co-Investigators: Professorin Dr. Daniela Berg; Professor Dr. Klaus Berger; Professor Dr. Wolfgang Lieb; Privatdozent Dr. Oliver Riedel